Enterprises, nowadays, offer a multitude of interaction channels to existing/potential customers (hereinafter referred to as ‘customers’) for facilitating customer interactions. For example, the enterprises provide a website or a web portal, i.e. a web channel, to enable the customers to locate products/services of interest, to receive information about the products/services, to make payments, to lodge complaints, and the like. In another illustrative example, the enterprises may offer dedicated customer sales and service representatives, such as for example live agents, to interact with the customers by engaging in voice conversations, i.e. speech channel, and/or chat conversations, i.e. chat channel. Similarly, the enterprises may offer other interaction channels such as an interactive voice response (IVR) channel, a social channel, and the like.
The enterprises, typically, seek to predict the intention of each customer accessing the interaction channels because prediction of the customer's intentions enables the enterprises to make suitable recommendations to the customers and thus enhance a customer service experience and/or improve the chances of making a sale. To predict intentions of customers accurately, data is collated corresponding to the customers and their interactions such as for example, data related to website surfing patterns, recent transactions, customer interests and preferences, past interaction with agents and the like. The collated data is used for profiling of customers into different user profiles based on certain commonality in their attributes. Appropriate business rules and/or predictive models are then used to predict intentions of customers, such as for example, intention to purchase a product and/or avail a service and the like. However, such profiling of customers based on certain commonality in their attributes may not necessarily reflect behavioral similarity, or similarity in goals and motives of the customers within the same profile. Accordingly, it would be advantageous to take customer behavioral attributes into account to provide personalized treatment to a customer.